Kaldi-asr-server

This is a flask asr-service with server and client, which is based on the Vernacular-ai/kaldi-serve(https://github.com/Vernacular-ai/kaldi-serve).

Key Features:

• Real-time streaming (uni & bi-directional) audio recognition.
• support MFCC and Fbank when the corresponding file exists
• support i-vector input when the corresponding file exists
• Thread-safe concurrent Decoder queue for server environments.
• support RNNLM lattice rescoring when the corresponding file exists.
• N-best alternatives with AM/LM costs, word-level timings and confidence scores.

Installation

• Kaldi
• python==3.6.7(suggest conda install)
• pybind11(https://github.com/pybind/pybind11) pybind11 is already included in the project, so you don't have to reconfigure it

Build from Source

config the KALDI_ROOT path in CMakeLists.txt
cd build/
cmake .. -DBUILD_PYBIND11=ON -DBUILD_PYTHON_MODULE=ON -DPYTHON_EXECUTABLE=${which python}
make -j${nproc}
cp python/kaldiserve_pybind*.so ../python/kaldiserve/
cd ../python
pip install . -U

Configuration

you should config the model files in "./resources/model-spec.toml" before you start the server.

Usage

cd python
Start the service: python server.py
Start the clinet with multithreading: python client_test.py

Reference

• https://github.com/Vernacular-ai/kaldi-serve
• https://github.com/al-zatv/kaldi-serve